Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid
In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrosp...
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| Published in: | Cancers Vol. 14; no. 2; p. 449 |
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| Main Authors: | , , , , , , , , , , , , , , , |
| Format: | Journal Article |
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| Abstract | In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease. |
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| AbstractList | In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease. Simple Summary The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches. In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease. Simple SummaryThe early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches. AbstractIn the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease. |
| Author | Lecrevisse, Quentin Lorenzo-Gil, Héctor Juanes-Velasco, Pablo Gongora, Rafael Nilsson, Peter Fuentes, Manuel Landeira-Viñuela, Alicia Galicia, Norma Jara-Acevedo, Ricardo Bareke, Halin Pedreira, Carlos Eduardo Pin, Elisa Orfao, Alberto Sanchez-Santos, Jose Manuel Carabias-Sánchez, Javier García-Valiente, Rodrigo |
| AuthorAffiliation | 3 Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 11428 Stockholm, Sweden; elisa.pin@scilifelab.se (E.P.); peter.nilsson@scilifelab.se (P.N.) 4 Immunostep S.L. Institute of Cancer Research, Av. Universidad de Coimbra, 37007 Salamanca, Spain; rjara@immunostep.com 6 Statistics Department, University of Salamanca, 37008 Salamanca, Spain; jose@usal.es 1 Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain; pablojuanesvelasco@usal.es (P.J.-V.); paola.galiciac@aefcm.gob.mx (N.G.); quentin@usal.es (Q.L.); rgongora@usal.es (R.G.); hectorlorenzogil@usal.es (H.L.-G.); alavi29@usal.es (A.L.-V.); halin.bareke@gmail.com (H.B.); orfao@usal.es (A.O.) 5 Systems and Computing Department (COPPE-PESC), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-914, Brazil; pedreira@cos.ufrj.br 2 Proteomics Unit, Cancer Research Centre-IBMC |
| AuthorAffiliation_xml | – name: 4 Immunostep S.L. Institute of Cancer Research, Av. Universidad de Coimbra, 37007 Salamanca, Spain; rjara@immunostep.com – name: 1 Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain; pablojuanesvelasco@usal.es (P.J.-V.); paola.galiciac@aefcm.gob.mx (N.G.); quentin@usal.es (Q.L.); rgongora@usal.es (R.G.); hectorlorenzogil@usal.es (H.L.-G.); alavi29@usal.es (A.L.-V.); halin.bareke@gmail.com (H.B.); orfao@usal.es (A.O.) – name: 2 Proteomics Unit, Cancer Research Centre-IBMCC, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain; jcarabias@usal.es (J.C.-S.); rodrigo.garcia.valiente@gmail.com (R.G.-V.) – name: 5 Systems and Computing Department (COPPE-PESC), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-914, Brazil; pedreira@cos.ufrj.br – name: 3 Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 11428 Stockholm, Sweden; elisa.pin@scilifelab.se (E.P.); peter.nilsson@scilifelab.se (P.N.) – name: 6 Statistics Department, University of Salamanca, 37008 Salamanca, Spain; jose@usal.es |
| Author_xml | – sequence: 1 givenname: Pablo orcidid: 0000-0001-9435-2952 surname: Juanes-Velasco fullname: Juanes-Velasco, Pablo organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 2 givenname: Norma surname: Galicia fullname: Galicia, Norma organization: Proteomics Unit, Cancer Research Centre-IBMCC, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 3 givenname: Elisa orcidid: 0000-0002-2158-2674 surname: Pin fullname: Pin, Elisa organization: Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 11428 Stockholm, Sweden – sequence: 4 givenname: Ricardo surname: Jara-Acevedo fullname: Jara-Acevedo, Ricardo organization: Immunostep S.L. Institute of Cancer Research, Av. Universidad de Coimbra, 37007 Salamanca, Spain – sequence: 5 givenname: Javier surname: Carabias-Sánchez fullname: Carabias-Sánchez, Javier organization: Proteomics Unit, Cancer Research Centre-IBMCC, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 6 givenname: Rodrigo surname: García-Valiente fullname: García-Valiente, Rodrigo organization: Proteomics Unit, Cancer Research Centre-IBMCC, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 7 givenname: Quentin surname: Lecrevisse fullname: Lecrevisse, Quentin organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 8 givenname: Carlos Eduardo orcidid: 0000-0002-9312-4023 surname: Pedreira fullname: Pedreira, Carlos Eduardo organization: Systems and Computing Department (COPPE-PESC), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-914, Brazil – sequence: 9 givenname: Rafael orcidid: 0000-0002-8046-4301 surname: Gongora fullname: Gongora, Rafael organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 10 givenname: Jose Manuel orcidid: 0000-0002-7434-7598 surname: Sanchez-Santos fullname: Sanchez-Santos, Jose Manuel organization: Statistics Department, University of Salamanca, 37008 Salamanca, Spain – sequence: 11 givenname: Héctor surname: Lorenzo-Gil fullname: Lorenzo-Gil, Héctor organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 12 givenname: Alicia surname: Landeira-Viñuela fullname: Landeira-Viñuela, Alicia organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 13 givenname: Halin orcidid: 0000-0003-4577-3325 surname: Bareke fullname: Bareke, Halin organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 14 givenname: Alberto orcidid: 0000-0002-0007-7230 surname: Orfao fullname: Orfao, Alberto organization: Deparment of Medicine and General Servive of Cytometry, Cancer Research Centre-IBMCC, CSIC-USAL, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain – sequence: 15 givenname: Peter surname: Nilsson fullname: Nilsson, Peter organization: Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, 11428 Stockholm, Sweden – sequence: 16 givenname: Manuel orcidid: 0000-0002-7305-3766 surname: Fuentes fullname: Fuentes, Manuel organization: Proteomics Unit, Cancer Research Centre-IBMCC, IBSAL, Campus Miguel de Unamuno s/n, University of Salamanca-CSIC, 37007 Salamanca, Spain |
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| CitedBy_id | crossref_primary_10_7759_cureus_55187 crossref_primary_10_1016_j_wneu_2024_04_049 crossref_primary_10_1177_11795549231205206 |
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| Copyright | 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2022 by the authors. 2022 |
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| Keywords | CSF-stabilizing reagents leptomeningeal metastasis (LM) LC-MS/MS tumor infiltrating cerebrospinal fluid (CSF) high-abundant protein depletion modelling leptomeningeal disease biomarkers protein-based biomarker protein microarrays proteomic analysis |
| Language | English |
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| Snippet | In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This... Simple SummaryThe early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to... Simple Summary The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to... |
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| SubjectTerms | Biomarkers Blood Brain cancer Brain research Cellular biology Central nervous system Cerebrospinal fluid cerebrospinal fluid (CSF) CSF-stabilizing reagents Diagnosis Disease Fc receptors Fluids high-abundant protein depletion LC-MS leptomeningeal metastasis (LM) Leukemia Life span Liquid chromatography Lymphoma Mass spectroscopy Medical prognosis Medical research Meninges Meningitis Metastases Metastasis modelling leptomeningeal disease Nervous system Pathology Prediction models Prognosis protein microarrays protein-based biomarker Proteins proteomic analysis Proteomics Tumor cells tumor infiltrating Tumors |
| Title | Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/35053611 https://www.proquest.com/docview/2621275697 https://search.proquest.com/docview/2622288135 https://pubmed.ncbi.nlm.nih.gov/PMC8773653 https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-308672 |
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